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Coordinating the cloud computing service supply chain under asymmetric demand information with quantity discount contract

机译：不对称需求信息下的云计算服务供应链与数量折扣契约的协调

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The article mainly examines coordinated strategies in a cloud computing service supply chain that faces random demand of a single product, and consists of one application infrastructure provider (AIP), one application platform provider (APP) and one application service provider (ASP). We consider a setting that the ASP has accurate demand information while the APP and AIP don't because they are relatively far away from the consumer market. In this paper, we examine the supply chain's performance mainly through discussing three situations: basic model (decentralized control) under asymmetric information, reference model (centralized control) and experimental model (quantity discount contract) under sharing demand information. We provide numerical results to compare the supply chain profits and conduct sensitivity analysis under three models. We find that using quantity discount contract can attain Pareto improvement. We also find that the ASP doesn't have motivation to transfer false demand information. Moreover, the numerical analysis and sensitivity analysis show that reducing the delay cost can improve the profits of the cloud computing service supply chain and its members. What is more, on the same level of delay cost, the impact of quantity discount on the expected profits improvement of upstream members is more than the downstream members.
机译：本文主要研究面向单个产品随机需求的云计算服务供应链中的协调策略，该战略由一个应用程序基础架构提供商（AIP），一个应用程序平台提供商（APP）和一个应用程序服务提供商（ASP）组成。我们认为，ASP具有准确的需求信息，而APP和AIP却没有，因为它们离消费者市场相对较远。在本文中，我们主要通过讨论三种情况来检验供应链的绩效：不对称信息下的基本模型（分散控制），共享需求信息下的参考模型（集中控制）和实验模型（数量折扣合同）。我们提供数值结果以比较供应链利润并在三种模型下进行敏感性分析。我们发现使用数量折扣合同可以实现帕累托改进。我们还发现，ASP没有动机来传递虚假的需求信息。此外，数值分析和敏感性分析表明，降低延迟成本可以提高云计算服务供应链及其成员的利润。此外，在相同水平的延迟成本下，数量折扣对上游成员的预期利润提高的影响要大于下游成员。

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